Air–water CH4 and CO2 fluxes were directly measured
using the eddy covariance technique at the Penlee Point Atmospheric
Observatory on the southwest coast of the United Kingdom from September 2015
to August 2016. The high-frequency, year-long measurements provide
unprecedented detail on the variability of these greenhouse gas fluxes from
seasonal to diurnal and to semi-diurnal (tidal) timescales. Depending on the
wind sector, fluxes measured at this site are indicative of air–water
exchange in coastal seas as well as in an outer estuary. For the open-water
sector when winds were off the Atlantic Ocean, CH4 flux was almost
always positive (annual mean of ∼0.05 mmol m-2 d-1) except
in December and January, when CH4 flux was near zero. At times of
high rainfall and river flow rate, CH4 emission from the
estuarine-influenced Plymouth Sound sector was several times higher than
emission from the open-water sector. The implied CH4 saturation
(derived from the measured fluxes and a wind-speed-dependent gas transfer
velocity parameterization) of over 1000 % in the Plymouth Sound is within
range of in situ dissolved CH4 measurements near the mouth of the
river Tamar. CO2 flux from the open-water sector was generally from
sea to air in autumn and winter and from air to sea in late spring and
summer, with an annual mean flux of near zero. A diurnal signal in
CO2 flux and implied partial pressure of CO2 in water
(pCO2) are clearly observed for the Plymouth Sound sector
and also evident for the open-water sector during biologically productive
periods. These observations suggest that coastal CO2 efflux may be
underestimated if sampling strategies are limited to daytime only. Combining
the flux data with seawater pCO2 measurements made in situ
within the flux footprint allows us to estimate the CO2 transfer
velocity. The gas transfer velocity and wind speed relationship at this
coastal location agrees reasonably well with previous open-water
parameterizations in the mean but demonstrates considerable variability. We
discuss the influences of biological productivity, bottom-driven turbulence
and rainfall on coastal air–water gas exchange.
Introduction
Methane (CH4) and carbon dioxide (CO2) are two of the
most important greenhouse gases (GHGs). Their tropospheric abundances have
increased over the last few hundred years primarily due to human activities,
with the fastest increases in the last 50 years (Hartmann et al., 2013).
Highly dynamic estuarine and coastal regions can be important sources and
sinks of these GHGs. Understanding the emissions and uptake of these gases by
coastal waters and how they change is directly relevant to the fulfillment of
the United Nations Framework Convention on Climate Change (UNFCCC) Paris 2016
agreement. We argue in this paper that the eddy covariance (EC) technique,
with a temporal resolution of tens of minutes to hours, is an excellent
method for long-term monitoring of coastal air–sea CH4 and
CO2 fluxes.
There has been much debate over the causes of the recent tropospheric
CH4 trend, from varying wetland (e.g. Pison et al., 2013; Schaefer
et al., 2016; Nisbet et al., 2016) and fossil fuel (e.g. Helmig et al., 2016;
Rice et al., 2016) emissions to changes in the atmospheric oxidative
capacity (e.g. Rigby et al., 2017). Inland aquatic systems may be important
sources of tropospheric CH4 (e.g. Borges et al., 2015). Similarly,
due to benthic methanogenesis, large surface CH4 supersaturations
of thousands of percent have been observed in estuaries (e.g. Upstill-Goddard
et al., 2000; Middelburg et al., 2002). CH4 concentrations in
estuaries can be influenced by processes including biological productivity,
organic-carbon input, benthic and particle-derived CH4 production,
oxygen content, and hydrodynamics (e.g. Upstill-Goddard et al.,
2000, 2016). In regions of intense benthic methanogenesis, gas bubbles
supersaturated with CH4 episodically rise through the water column
to the surface (e.g. Dimitrov, 2002; Kitidis et al., 2007). This process of
ebullition will result in CH4 emissions that are not quantified
using air–sea flux calculations based on seawater CH4 concentration
(see below). In coastal seas, CH4 saturation tends to be lower than
in estuaries but is still much greater than 100 % (e.g. mean
> 200 % for European shelf waters; Bange et al., 2006).
Consequently, estuaries and coastal seas tend to have much greater
CH4 emissions per unit area than the open ocean (Bange et al.,
2006; Forster et al., 2009).
Seawater CO2 levels are primarily determined by solubility
(temperature-dependent) and the balance between primary production and
respiration by the biological community. Seasonal and geographical
differences in seawater temperature and biological activity mean that the
surface ocean can act as a net source or sink of CO2, depending on
location and time of the year (Khatiwala et al., 2013; Houghton, 2003).
Models estimate that 2.4±0.5 GtC yr-1 of CO2 (a quarter
of anthropogenic emissions) have been absorbed by the global ocean over the
last decade (Le Quéré et al., 2018). Shelf seas, despite their
relatively small area, support high primary productivity, cause a large
drawdown of CO2 in the mean (Frankignoulle and Borges, 2001; Chen
et al., 2013) and might be responsible for as much as 10 %–40 % of
global oceanic carbon sequestration (Muller-Karger et al., 2005; Cai et al.,
2006; Chen et al., 2009; Laruelle et al., 2010). Estuaries, on the other
hand, are generally net sources of CO2 to the atmosphere (e.g.
Frankignoulle et al., 1998). Inner estuaries are estimated to emit about
0.3 GtC yr-1 of CO2 globally (Laruelle et al., 2010; Cai
2011). Most of this CO2 emission is due to the degradation of
allochthonous organic matter rather than a direct input of dissolved
inorganic carbon (Borges et al., 2006). The direction of net air–sea
CO2 flux is less certain in coastal areas that are influenced by
riverine outflow and anthropogenic activities (Chen et al., 2013). Kitidis et
al. (2012) showed a gradient of increasing air-to-sea CO2 flux with
distance offshore in the western English Channel. The coastal seas may have
been heterotrophic during preindustrial conditions and thus a net source of
CO2 due to organic-carbon degradation (e.g. Smith and Hollibaugh,
1993). Some studies (e.g. Andersson and Mackenzie, 2004; Cai, 2011) predict
that shallow seas will become a net sink (or a reduced source) of
CO2 in the future due to rising atmospheric CO2 levels
and increased inorganic nutrient inputs. Modelling of the carbonate chemistry
and hence CO2 flux in the northwestern European shelf is hindered
partly because of the uncertain representation of riverine influence (Artioli
et al., 2012).
To quantify the impacts of estuarine and coastal emissions on the atmospheric
CH4 and CO2 burden, an indirect method requiring the
inventories of air–sea concentration difference (ΔC) and the gas
transfer velocity (K) is usually utilized: Flux =K⋅ΔC.
Coastal areas tend to be highly dynamic, with greater spatial and temporal
variability in physics and biology than the open ocean. This heterogeneity
poses serious challenges to observational and modelling efforts aimed at
constraining coastal air–sea GHG fluxes. Dissolved gas concentrations may be
affected by tides, currents, mixed-layer processes and benthic–pelagic
interactions. The sheltered nature of the coastal seas, coupled with
freshwater input, often results in stratification (e.g. Sims et al., 2017),
where biological processes can more quickly modify the near-surface dissolved
gas concentrations. Mixed-layer dynamics can vary on a diurnal timescale, due
for example to buoyancy forcing (e.g. Esters et al., 2018). The atmospheric
concentrations of GHGs at coastal locations also vary as a function of wind
direction, air mass history and boundary layer processes (e.g. Yang et al.,
2016a). Estuaries and coastal seas in mid-latitudes also tend to experience
large seasonal variability, which affects the dissolved gas concentrations
(e.g. Crosswell et al., 2012; Joesoef et al., 2015).
The transfer velocity (K) primarily depends on near-surface turbulence, and
over the ocean it is generally parameterized as a function of wind speed (e.g.
Wanninkhof et al., 2009). Currents and resultant bottom-driven turbulence
significantly affect gas exchange in shallower waters, resulting in K
values that can be much higher than predicted based on wind speed alone
(O'Connor and Dobbins, 1958; Borges et al., 2004; Ho et al., 2014). Rainfall
is highly episodic but may be important for gas exchange because it
generates additional turbulence and/or alters near-surface gas concentrations
(e.g. Ho et al., 1997; Zappa et al., 2009; Turk et al., 2010). Variability in
biogeochemical processes could also affect K by changing the surface
tension and modifying the turbulence at the air–sea interface. Pereira et
al. (2016) observed a gradient of increased sea surface surfactant activity
from the open sea towards the coast, which reduced the gas transfer velocity
by approximately a factor of 2 in their laboratory tank simulations. Thus, a representation of K dependent on wind speed only is probably even less
appropriate for coastal environments than for the open ocean.
Measuring the fluxes directly with the eddy covariance technique is an ideal
way to study the many controlling factors of air–sea exchange in dynamic and
heterogeneous environments such as shallow waters and coastal seas. It also
allows us to test the appropriateness of the indirect flux calculations.
Furthermore, compared to shipboard EC observations, measuring fluxes from a
stationary tower has the advantage of not requiring any motion correction on
the winds (see Edson et al., 1998). This means that flux and K measurements
at a coastal location are potentially more accurate, especially at high wind
speeds when the motion correction for a moving platform would become large.
Only a few coastal stations exist worldwide that have reported air–sea
CO2 fluxes by EC on a seasonal timescale, such as
Östergarnsholm station in the Baltic Sea (Rutgersson et al., 2008), the
Utö Atmospheric and Marine Research Station also in the Baltic Sea
(Honkanen et al., 2018), Punta Morro in Baja California, Mexico
(Gutieìerrez-Loza and Ocampo-Torres, 2016) and Qikirtaarjuk Island in
the Canadian Arctic (Butterworth and Else, 2018). In the case of the
Östergarnsholm station, concurrent measurements of the partial pressure of
seawater CO2 (pCO2) from a nearby buoy allow for
the determination of the CO2 gas transfer velocity. CH4
sensors with sufficient measurement frequency and precision for the EC
methods have only been developed in recent years (Yang et al., 2016b). We are
not aware of any published long-term air–sea CH4 fluxes by the EC
method.
In this paper, we describe a year-long set of air–water CO2 and
CH4 flux measurements by EC at the coastal Penlee Point Atmospheric
Observatory. The high-frequency fluxes allow us to characterize their
variability across a range of timescales (semi-diurnal to diurnal to
seasonal). Combining these data with in situ observations of dissolved gas
concentrations as well as supporting physical and biogeochemical
measurements enables us to quantify the gas transfer velocity at this
coastal location and examine its controls.
Experimental
The Penlee Point Atmospheric Observatory (PPAO; 50∘19.08′ N,
4∘11.35′ W;
http://www.westernchannelobservatory.org.uk/penlee/, last access:
7 March 2019) was established in May 2014 on the southwest coast of the
United Kingdom. Understanding the controls of coastal air–sea exchange is
one of the main scientific foci at this site. Yang et al. (2016a, b)
demonstrated that the PPAO is a suitable location to measure air–sea
exchange by the EC method.
Eddy covariance fluxes
Atmospheric CH4 and CO2 mixing ratios were measured at a
frequency of 10 Hz using a Los Gatos Research (LGR) Fast Greenhouse Gas
Analyzer (FGGA, enhanced performance model) between September 2015 and
August 2016. As described in detail by Yang et al. (2016a), two Gill sonic
anemometers (Windmaster Pro and R3) are installed on a mast on the rooftop of
PPAO (∼18 m above mean sea level). For this paper, wind data from the
Windmaster Pro sonic anemometer were used between September 2015 and
March 2016. Since March 2016, wind data from the R3 sonic anemometer (not
operational for the first 6 months of this annual study) were preferred
because of its higher precision and better performance during heavy rain
events. The effect of rain on the EC gas flux measurement is discussed in the
Supplement.
The gas inlet tip, located ∼30 cm below the Windmaster Pro sonic
anemometer centre volume, is connected to the LGR via ∼18 m long
perfluoroalkoxy (PFA) tubing (3/8′′ outer diameter). First a scroll pump
(BOC Edwards XDS-35i) until 16 October 2015 and then a rotary vane pump (Gast
1023) were used to pull sample air through the inlet tubing, an aerosol
filter (2 µm pore size, Swagelok SS-6F-05) and the LGR. The aerosol
filter became laden with sea salt over time and the filter elements were
replaced approximately every ∼2 months. As a result, the volumetric
flow rate through the LGR varied between 23 and 78 LPM (litres per minute),
which affected the lag time and the high-frequency attenuation of the fluxes.
The lag time was determined from a maximum lag correlation analysis between
CO2 and the instantaneous vertical wind velocity (w), varying
from about 2.7 to 9.0 s. The strong atmosphere-biosphere flux of
CO2 when winds were from land aided our determination of this lag
time. The high-frequency flux attenuation was estimated from the instrument
response time (see Yang et al., 2013, 2016a) and a wind-speed-dependent
correction was applied to the flux data (representing a ∼15 % gain
in the mean).
Fluxes of CH4 and CO2 were initially computed in 10 min
intervals from the covariance of their lag-shifted dry mixing ratios and w.
Wind velocities were streamline corrected using the standard double-rotation
method (Tanner and Thurtell, 1969) on a 10 min basis. Evaluations of the EC
momentum transfer against the expected rate (Fig. S2 in Supplement), as well
as stationarity in winds and gas mixing ratios, are used to quality control
the 10 min flux data. The filtered 10 min fluxes are further averaged to
hourly and also 6-hourly intervals to reduce random noise. See Yang et
al. (2016a, b) for further details on data processing, quality control, and
measurements of momentum and sensible heat fluxes. Horizontal wind speed
measurements are corrected for flow distortion and adjusted to a neutral
atmosphere at 10 m height (see Supplement).
Flux footprints
The theoretical flux footprint model of Kljun et al. (2004) predicts the
upwind distance of maximum flux contribution (Xmax) and the
distance of 90 % cumulative flux contribution (X90). The
semi-diurnal tidal range at this location is large (up to 6 m during spring
tide), effectively raising the EC measurement height above water at low tide
and reducing it at high tide. For a neutral atmosphere, the Kljun et
al. (2004) model estimates Xmax and X90 to be approximately
0.4 and 1.1 km at the highest tide and 0.6 and 1.6 km at the lowest tide.
As described in more detail by Yang et al. (2016a), stable and unstable
atmospheres are predicted to increase and decrease Xmax as well
as X90 by a few tens of percent, respectively.
In this paper we focus on air–water transfer over two different wind
sectors. When winds are from the southwest (180–240∘), the eddy
covariance flux footprint is over open water with a depth of approximately
20 m at Xmax. When winds are from the northeast
(45–80∘), the footprint is over the fetch-limited Plymouth Sound
(approximately 5–6 km wide), which is ∼10 m deep and more influenced
by the outflow of the Tamar estuary (Siddorn et al., 2003; Uncles et al.,
2015). See Fig. S1 for a map of the site and the approximate flux footprints.
Seawater measurements
We used the Plymouth Marine Laboratory's research vessels (RVs)
Quest and Plymouth Explorer to study the spatial
heterogeneity in this coastal environment. Underway seawater measurements on
the Quest from ∼3 m depth include pCO2
(Kitidis et al., 2012), salinity, temperature, chlorophyll and dissolved
oxygen. As a part of the Western Channel Observatory sampling program
(http://www.westernchannelobservatory.org.uk, last access:
7 March 2019), the Quest made approximately weekly trips to the L4
station (50∘15.0′ N, 4∘13.0′ W; ∼6 km south of
PPAO) and fortnightly trips to the E1 station (50∘02.6′ N,
4∘22.5′ W; ∼20 km south of PPAO). These visits were always
during the daytime. On the way back to Plymouth from L4 and E1, the
Quest often idled at about 600 m to the south/southwest of PPAO for
approximately 10 min, enabling the collection of underway measurements
within the open-water flux footprint of PPAO. The ship also passed through
the Plymouth Sound flux footprint of PPAO en route back into port.
Seawater samples were taken at the L4 station from a CTD rosette. For
CH4 analysis, discrete seawater samples were collected directly
into 500 mL borosilicate bottles from Niskin bottles using clean Tygon
tubing. Sample bottles were overfilled by 3 times their volume to eliminate
air bubbles, poisoned with 100 µL of a saturated mercuric chloride
solution and returned to the laboratory where they were transferred to a
water bath at 25 ∘C and temperature equilibrated for a minimum of
1 h before analysis. Samples were analysed for CH4 by single-phase
equilibration gas chromatography using a flame ionization detector similar to
that described by Upstill-Goddard et al. (1996). Samples were typically
analysed at Plymouth Marine Laboratory (PML) within 2 weeks of collection and
calibrated against three certified (±5 %) reference standards (Air
Products Ltd), which are traceable to NOAA WMO-N2O-X2006A.
The other PML vessel, a hard-bottomed Rigid Hull Inflatable Boat (RHIB,
Plymouth Explorer), was used to occasionally sample the estuary
Tamar from the upper freshwater section near Gunnislake to the lower
saltwater section near the Plymouth Sound in 2017 and 2018. This is a part of
the NERC-funded LOCATE (Land Ocean Carbon Transfer;
http://www.locate.ac.uk, last access: 7 March 2019) research programme.
Discrete seawater samples were collected at stations from the near surface
into 500 mL borosilicate bottles with care taken to eliminate air bubbles.
Analysis for dissolved CH4 was performed as described above.
Results and discussion
Over the 1 year of measurements, variability in physical parameters was
large: wind speed at times exceeding 20 m s-1, and seawater
temperature varying between about 7 ∘C and 18 ∘C.
Chlorophyll a concentration ranged between about 0.2 and 5 mg m-3,
with generally higher values from late spring to early autumn than in winter.
Time series of ancillary data (meteorological parameters, Tamar river flow,
and surface ocean physical and biogeochemical parameters) are shown in the
Supplement (Figs. S3 to S6). This region can be roughly characterized by a
windier, wetter autumn and winter and a calmer, dryer spring and summer.
Southwesterly winds off the Atlantic Ocean (annual mean wind speed of ∼8 m s-1) occurred more frequently in the winter months, resulting in
higher precipitation rates and greater riverine discharge. During these
conditions, the temperatures in the sea surface and air were similar
throughout the entire year, resulting in fairly small air–sea temperature
differences and modest sensible heat fluxes (monthly average of typically
-20 to 20 W m-2). As a result, the atmosphere was often close to
neutral stability with a monthly mean Monin–Obukhov stability parameter
(z/L) between -1.7 and 0.04.
Figure 1 shows the air–sea flux of CH4 over the 1-year
measurement period. Flux data gaps are due to either wind direction outside
of air–water sectors or instrumental failure. As shown by Yang et
al. (2016b), under ideal conditions (moderate winds and steady atmospheric
mixing ratio) the random uncertainty in the LGR CH4 flux due to
band-limited instrumental noise is on the order of 0.02 and
0.01 mmol m-2 d-1 for a 1 h average and a 6 h average,
respectively. In comparison, the standard deviation (σ) in the
6 h averaged CH4 flux for the open-water sector is about
0.05 mmol m-2 d-1 (computed over the entire year). Thus, much of
the rapid temporal fluctuations in the measured CH4 flux appear to
be driven by natural variability (due to changes in water mass within the flux
footprint, wind, etc.), rather than due to random instrumental noise.
CH4 flux from the open-water sector at times shows semi-diurnal
(tidal) variability (consistent with Yang et al., 2016a). We note that most
of what appear to be negative CH4 fluxes are within the uncertainty
of the EC measurement and are not significantly different from zero.
One-year time series of CH4 flux (hourly average) during
times when winds were from the sea. Six-hour averages of fluxes are further
separated into the southwest (open water) and northeast (Plymouth Sound) wind
sectors. Error bars indicate standard error.
To more clearly illustrate the seasonal variability, the means and 25th and 75th
percentiles of the 6 h averaged CH4 fluxes are computed in
monthly intervals (Fig. 2). CH4 flux was consistently positive,
indicating emission of CH4 from these coastal waters. The only
exception was during the months of December and January, when CH4
flux was near zero. The annual mean CH4 flux from the open-water
sector was 0.047 (standard error, or SE, of 0.008) mmol m-2 d-1
when computed from monthly mean fluxes and 0.039 (SE of
0.003) mmol m-2 d-1 when directly computed from 6 h mean
fluxes. Wind directions that enable air–sea flux measurements did not occur
with the same frequency throughout the year. For example, southwesterly winds
were less frequent in spring (30 % of the time in March–May 2016) than in
winter (60 % of the time in January 2016). Thus, annual averages computed
directly from the 6 h fluxes are more heavily weighted by the periods
with a high proportion of valid flux measurements. In contrast, annual
averages computed from the monthly means give more equal weight to all the
months. The annual mean CH4 flux here is largely consistent with
previous coastal estimates (e.g. Upstill-Goddard et al., 2016) and roughly 1 order of magnitude greater than estimates of CH4 flux for the open
ocean (e.g. Forster et al., 2009).
Monthly averages and 25th and 75th percentiles
(designated 25/75 % in the
figure) of CH4 flux from the southwest (open water) and northeast
(Plymouth Sound) wind sectors. Error bars indicate 2 times standard error.
Monthly averages and 25th and 75th percentiles of implied
CH4 concentration for the southwest (open water) and northeast
(Plymouth Sound) wind sectors, along with the equilibrium value with respect
to the atmosphere.
CH4 flux from the Plymouth Sound sector was noticeably higher than
flux from the open-water sector, with an annual mean of about 0.108 (SE of
0.026) mmol m-2 d-1. This enhancement in the flux was
particularly noticeable at times of high rainfall and river discharge rate,
with fluxes over 0.2 mmol m-2 d-1 in February 2016. During the
dry summer months of 2016 (May and June), CH4 fluxes from the two
wind sectors were comparable. Northerly winds occurred only 7.4 % of the
time overall during the 1-year study period. Thus, the seasonal variability
in CH4 emission from the Plymouth Sound is less well represented
than emission from the open-water sector.
We briefly compare our measured fluxes with existing estimates of riverine
CH4 emission. The 1 km2 resolution UK National Atmospheric
Emissions Inventory (NAEI, http://naei.defra.gov.uk, last access:
7 March 2019) reports a natural CH4 emission source of
0.17 mmol m-2 d-1 averaged over the area of the Plymouth Sound
for the year 2013. Our annual mean flux from the Plymouth Sound wind sector
is about 64 % of the NAEI estimate. Based on in situ measurements of
dissolved CH4 concentrations in six major UK estuaries,
Upstill-Goddard et al. (2016) estimated CH4 emissions of
4.3 Gg yr-1 for UK outer estuaries (using a total outer estuarine area
of 1894 km2). If we crudely assume that the Plymouth Sound is a
representative outer UK estuary, scaling up our mean flux from this wind
sector to the total outer estuarine area of 1894 km2 yields an annual
flux of 1.2 Gg yr-1. This is lower than the estimate from
Upstill-Goddard et al. (2016), likely because according to their survey the
CH4 saturation from the Tamar is fairly low compared to some of the
other major UK estuaries. The UK has a 12 429 km long coastline. If the
PPAO open-water footprint is representative of the nearest 1.4 km (i.e.
typical X90 of our fluxes; see Sect. 2.2) of the UK coast, our
measurements crudely extrapolate to a total CH4 flux of
4.8 Gg yr-1 for the UK coastal seas. This order-of-magnitude estimate
is made from a mean flux of 0.047 mmol m-2 d-1 and a total
coastal sea area of 12 429 km by 1.4 km. We are not able to use PPAO EC
flux data to provide estimates for CH4 emission from the inner
estuary, where fluxes are likely higher per unit area (Upstill-Goddard et
al., 2016).
We wish to disentangle the processes that control the gas transfer velocity
(K) from the processes that control the air–water concentration difference
(ΔC). We first compute the implied seawater CH4 and
CO2 concentrations from the eddy covariance fluxes by assuming a
parameterization of the gas transfer velocity. Here the sea-minus-air
concentration difference (ΔC) is computed by dividing the EC flux by
the wind-speed-dependent K from Nightingale et al. (2000) (adjusted for
ambient Schmidt number by the exponent of -0.5). Adding the atmospheric
concentration to ΔC yields the implied seawater concentration. At low
wind speeds, both the flux and K trend towards zero. To avoid excessive
noise from dividing one small number by another, implied seawater
concentrations at wind speeds lower than 5 m s-1 are discarded. Note
that we apply the Nightingale et al. (2000) wind-speed-based K
parameterization here largely because it is commonly used and lies between
the very strong and the very weak wind-speed-dependent relationships.
Implied seawater CH4 concentration from the open-water flux
footprint ranges from about 3 to 26 nM on a monthly interval (mean of
14 nM; see Fig. 3). It is often convenient to represent dissolved
CH4 as a saturation level relative to the atmosphere
(saturation =CH4w/(CH4a⋅solCH4)⋅100, where CH4w and CH4a
are waterside and airside concentrations; solCH4 is the
CH4 solubility from Wanninkhof, 2014). CH4 saturations
are shown in Fig. S8. The lowest implied CH4 concentration occurred
in winter and corresponded to a saturation level close to 100 %. The
highest implied CH4 concentration was from April to November, with
an average saturation level of about 600 %. The temperature and
salinity-dependent solubility of CH4 varies by only ∼14 %
from summer to winter at this location. The seasonal variability in
CH4 concentration and saturation is thus more due to changing
biological processes (methanogenesis and/or CH4 oxidation) and
hydrodynamics than due to dissolution (i.e. seasonal temperature changes).
For the Plymouth Sound flux footprint, the implied concentration ranges from
9 to 99 nM (mean of 37 nM, corresponding to about 1200 % saturation),
with the highest values in late winter and early spring. These implied
concentrations and saturations are compared with nearby dissolved
CH4 measurements in Sect. 3.3.3. We note that any contribution to
CH4 emission from ebullition would have been included in the EC
flux measurements, potentially resulting in higher implied seawater
CH4 concentrations than the measured dissolved concentrations.
Based on measurements from April to June 2015 at PPAO, Yang et al. (2016a)
observed that CH4 flux from the open-water flux footprint varied
with the timing of the tide but not with the tide height. Specifically,
CH4 flux tended to be the highest during the first ∼4 h
after low water. This was attributed to the outflow of a lower-salinity
surface layer from the Tamar river during rising tide around the Penlee
headland. A subtle semi-diurnal variability in CH4 flux can be seen
in Fig. 6b, where adjacent 6 h mean fluxes always alternated between
higher and lower values during these few days. The same general tidal pattern
is apparent over an annual cycle in the implied saturation level of
CH4. On average, the implied CH4 saturation within the
open-water sector was about 40 % higher during rising tide than during
falling tide.
One-year time series of CO2 flux (hourly average) during
times when winds were from the sea. Six-hour averages are further separated
into the southwest (open water) and northeast (Plymouth Sound) wind sectors.
Error bars indicate standard error.
Figure 4 shows the air–sea flux of CO2 over the 1-year
measurement period. The random uncertainty in the LGR CO2 flux,
estimated from the band-limited instrumental noise, is on the order of 4 and
2 mmol m-2 d-1 for 1 h average and 6 h average
measurements, respectively (Yang et al., 2016b). The standard deviation in
the 6 h averaged CO2 flux for the open-water sector is about
20 mmol m-2 d-1 (computed over the entire year), substantially
greater than the random uncertainty due to instrumental noise. The rapid
temporal fluctuations in CO2 flux are likely to be driven by
variability in winds as well as variability in seawater
pCO2. The latter is unlikely to be fully captured by
weekly or monthly seawater sampling.
The means and 25th and 75th percentiles of the 6 h averaged CO2
fluxes are computed in monthly intervals (Fig. 5). CO2 flux from
the open-water sector was generally from sea to air in autumn and winter (up
to 37 mmol m-2 d-1) and from air to sea in spring and
early summer (as much as -26 mmol m-2 d-1). The seasonality in
CO2 flux is consistent with seawater pCO2
observations by Litt et al. (2010) and Kitidis et al. (2012) from the same
region and is partly driven by biology. Figure S7 shows that in situ
pCO2 generally decreased with increasing chlorophyll a
concentrations during this annual study. CO2 flux from the Plymouth
Sound sector appeared to be more positive than from the open-water sector in
some months.
Monthly averages and 25th and 75th percentiles of CO2 flux from
the southwest (open water) and northeast (Plymouth Sound) wind sectors. Error
bars indicate 2 times standard error.
Example of variability in: (a)CO2 flux and
computed transfer velocity; (b)CH4 flux and sensible heat
flux; and (c) wind speed and tidal height during a period of
southwesterly winds. Fluxes are shown in both hourly and 6 h averages. Note
that the negative transfer velocity (K) values at night (shaded) computed
from the measured CO2 flux and interpolated daytime
pCO2 are non-physical, and likely due to unaccounted for
diurnal variability in seawater pCO2.
A 3-day time series of CO2 flux from July 2016 is shown in
Fig. 6a. Winds were consistently from the southwest during this period,
varying from about 3 to 12 m s-1 (Fig. 6c). CO2 flux during
this period was clearly different between day (mean of about
-13 mmol m-2 d-1) and night (mean of about
+9 mmol m-2 d-1), with an overall mean of about
-2 mmol m-2 d-1. Daytime pCO2 measurements
on the Quest from the 7 and 12 July imply a ΔpCO2 of about -40 µatm and a net flux into the
water. The EC flux is consistent in sign with ΔpCO2
during the day but not at night. The computed transfer velocity of
CO2 (KCO2,660, see Sect. 3.4) using the linearly
interpolated daytime pCO2 measurements yielded positive
values during the day (as expected) but negative values at night (which is
not physically possible). The positive CO2 flux at night is
unlikely to be caused by a nocturnal flux footprint that overlaps with land
because both sensible heat and CH4 fluxes are consistent with
air–sea exchange. The air temperature was about 1.2 ∘C warmer than
the water temperature, implying a slightly stable atmosphere and a flux
footprint that extends a few tens of percent further upwind from the PPAO
site than in a neutral atmosphere (Kljun et al., 2004). The measured sensible
heat flux averaged -9 W m-2 and showed little diurnal variability.
Similarly, CH4 flux was positive (sea to air) and did not vary with
the time of day.
The most likely reason for the negative nighttime KCO2,660 is that
seawater pCO2 varied diurnally, probably due to a
combination of biological and dynamical processes. Wind speed was generally
higher at night during these few days and the measured fluxes imply that the
actual ΔpCO2 changed from about -40 µatm
during the day to about 15 µatm at night. Similar diurnal cycles
(with slightly reduced magnitudes) have been observed in
pCO2 measurements in the western English Channel by Marrec
et al. (2014) and Litt et al. (2010). We note that a daytime CTD cast on
12 July 2016 showed a mixed layer at the L4 station of only ∼10 m
depth. Entrainment of deeper water could contribute towards a higher surface
pCO2 at night. A diurnal cycle in CO2 flux was
not obvious during times of expected evasion (sea-to-air flux). These periods
of positive CO2 flux occurred in autumn and winter when biological
productivity was low and the water column was mixed to the bottom.
The annual mean CO2 flux was 3.9 (SE of
4.9) mmol m-2 d-1 when computed from monthly mean fluxes
(Fig. 5) and 1.3 (SE of 1.3) mmol m-2 d-1 when directly computed
from 6 h mean fluxes. If we subsample our EC observations to the period
of 10:00–16:00 UTC only, the annual mean CO2 flux becomes 2.5 (SE
of 4.9) mmol m-2 d-1 when computed from monthly mean fluxes and
-1.0 (SE of 2.2) mmol m-2 d-1 when directly computed from
6 h mean fluxes. These results highlight the value of continuous flux
measurements and suggest that CO2 flux estimates based only on
daytime pCO2 measurements may be biased towards greater
seawater net uptake for coastal environments such as the western English
Channel.
Monthly averaged implied seawater CO2 concentrations from the two
flux footprints are shown in Fig. 7. The greatest supersaturation in
CO2 is observed in late autumn in the open-water sector, with
values exceeding 500 µatm. The greatest undersaturation in
CO2 is observed in late spring and early summer, coinciding with an
increase in chlorophyll a concentration at the nearby L4 station (Fig. S6).
Average implied pCO2 within the Plymouth Sound is
32 µatm higher than pCO2 within the open-water
flux footprint during months when fluxes were available for both wind
sectors. This difference between the outer estuary and the coastal seas
qualitatively agree with previous observations of supersaturated
pCO2 in the river Tamar (Frankignoulle et al., 1998).
Monthly averages and 25th and 75th percentiles of implied seawater
pCO2 for the southwest (open water) and northeast
(Plymouth Sound) wind sectors. Observed pCO2 from the
Plymouth Quest within the southwest sector (plus at L4) and within the
northeast sector are also shown, along with the equilibrium value with
respect to the atmosphere.
Average implied seawater CO2 saturation for the open-water sector
over the entire year is about 100 % in the daytime and slightly higher at
night (Fig. 8). In contrast, a marked diurnal variability in CO2
saturation is observed for the Plymouth Sound sector, with a higher
saturation level at night than during the day. Compared to the open-water
sector, Plymouth Sound is more sheltered and influenced by the Tamar outflow and thus subject to greater near-surface stratification and possibly different
biological processes. The diurnal variability we observed is important in the
context of estuarine CO2 (and carbonate system) observations that
are only carried out during daytime. Our findings suggest that such a
daytime-only monitoring strategy may underestimate estuarine
pCO2 and by extension the efflux of CO2 to the
atmosphere.
Mean diurnal variability in the implied seawater saturation of
CO2 for the for the southwest (open water) and northeast (Plymouth
Sound) wind sectors. Error bars indicate standard errors.
Semi-diurnal variability as a result of the tide is not obvious in the
CO2 flux or the implied CO2 saturation. This suggests
that the influence of the Tamar estuary on pCO2 within the
PPAO flux footprints is limited, consistent with the in situ
pCO2 measurements (see Sect. 3.3.2). The diurnal
variability in pCO2 might also be confounding any
semi-diurnal tidal signal.
It is worth noting that our implied seawater GHG concentrations would be
overestimated if the in situ gas transfer velocity were higher than the wind-speed-dependent parameterization of Nightingale et al. (2000). For example,
bottom-driven turbulence could enhance the gas transfer velocity (e.g. Borges
et al., 2004; Ho et al., 2014). We discuss the effects of depth and current
velocity on gas exchange in Sect. 3.4.3.
Spatial homogeneity of the study region
The estimation of the gas transfer velocity K requires concurrent
measurements of flux and seawater concentration within the flux footprint.
Seawater pCO2 was typically measured once or twice a week,
and only some of the measurements were made within the PPAO flux footprints.
Observations of dissolved CH4 were even scarcer and unfortunately
none of them were made within the flux footprints. In order to relate the
high-frequency EC fluxes to the discrete in situ dissolved gas
concentrations, we first evaluate the spatial homogeneity of our study region
using shipboard seawater measurements.
Variability in salinity
Previous modelling studies (Siddorn et al., 2003; Uncles et al., 2015) show
that freshwater discharge from the Tamar estuary mainly flows along the
western edge of Plymouth Sound and bends around PPAO towards the southwest.
In Fig. 9, we compare underway salinity measured within the PPAO flux
footprints (open water to the southwest as well as the Plymouth Sound to the
northeast) with near-coincidental Quest observations at the L4
station (6 km south of PPAO). Compared to the L4 station, mean salinity was
1.2 % and 2.1 % lower in the open water and Plymouth Sound
footprints, respectively. Periods of low salinity both within the footprints
and at L4 coincided with the greatest outflow from the Tamar estuary. These
observations indicate that the Tamar outflow influences this entire region;
unsurprisingly water is generally fresher within the Plymouth Sound than in
the open-water flux footprint. We next assess how much this riverine outflow
affects the seawater CO2 and CH4 concentrations within
the flux footprints of PPAO and thus the measured fluxes.
Salinity measured within the two air–water flux footprints of Penlee
vs. near-coincidental measurements from the Quest at the L4 station.
The size of the markers corresponds to the flow rate in the Tamar river, as
measured at Gunnislake.
Variability in seawater <inline-formula><mml:math id="M321" display="inline"><mml:mrow class="chem"><mml:mi>p</mml:mi><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
The underway in situ pCO2 measured within the PPAO flux
footprints is compared with near-coincidental observations from the
Quest at the L4 station in Fig. 10. The highest
pCO2 measured both within the footprints and at L4
occurred at times of large riverine discharge. This is seemingly consistent
with a Tamar influence (e.g. Frankignoulle et al., 1998) but may also be
driven by the seasonality in pCO2 (Kitidis et al., 2012).
As shown in Figs. S9–S11, fast responding sea surface temperature and
chlorophyll a were not noticeably different between the flux footprints and
L4, while dissolved oxygen was slightly lower within the footprints.
pCO2 measurements within both flux footprints were very
similar to pCO2 at the L4 station. The apparent agreement
for pCO2 could be in part because the measurement with a
“shower head” equilibrator has an integration time of 8 min (Kitidis et
al., 2012). The Quest usually only idled for ∼10 min within
the open-water flux footprint and did not idle within the Plymouth Sound
footprint. It is possible that the pCO2 spatial
variability is under-represented in the pCO2 measurements
due to the fairly slow response time of the equilibrator.
pCO2 measured within the two air–water flux
footprints of Penlee vs. near-coincidental measurements from the
Quest at the L4 station. The size of the markers corresponds to the
flow rate in the Tamar river, as measured at Gunnislake.
In situ pCO2 measurements from the Plymouth Sound
footprint and from the open-water footprint (plus L4, since they are not
distinguishable) are shown in Fig. 7, along with the 100 % saturation
value with respect to the atmosphere. Implied pCO2 for the
open-water sector and the in situ pCO2 within the open-water footprint (plus L4) broadly agree. Constraining the implied
pCO2 estimate to during the day further improves the
agreement with the in situ pCO2 measurements (also daytime
only; see Sect. 3.2). These observations suggest that the direct impact of
the Tamar outflow on pCO2 in the open-water flux footprint
at PPAO is fairly small relative to the air–sea concentration difference as
well as other sources of variability.
Variability in dissolved <inline-formula><mml:math id="M339" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CH</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
Dissolved CH4 was not measured within either of the PPAO flux
footprints. Here we look at how our implied CH4 concentrations from
the fluxes compare to measurements of dissolved CH4 in the river
Tamar and at L4. On four separate days in April 2017, July 2017,
January 2018 and April 2018, the Plymouth Explorer was used to
sample dissolved CH4 from the upper reaches of the Tamar to the
seaward end during a falling tide. CH4 in the estuarine part of
the Tamar in general correlated inversely with salinity (Fig. 11). For
example, in April 2017 the CH4 concentration was 491 nM at a
salinity of 4.7 (upper Tamar), 274 nM at a salinity of 29.3 (lower Tamar),
15 nM at a salinity of 34.2 (at the mouth of the Tamar in the Plymouth
Sound) and 2.4 nM at a salinity of 35.2 (L4). These correspond to
CH4 saturation values of ∼10000 % at a salinity of 29.3
and ∼600 % at a salinity of about 34.2 during this transect. The
highest CH4 concentration was measured in July 2017 following heavy
rainfall, while relatively low CH4 were observed in January and
April 2018. The measurements from the river Tamar in 2001 by Upstill-Goddard
et al. (2016) are within the range of these more recent transects. Long-term
observations of surface dissolved CH4 at L4 between October 2013
and July 2017 indicate a mean (±σ) saturation of 123±60 %.
Dissolved CH4 concentration from the Tamar river to the L4
station varies with salinity. Data from 2017 and 2018 were made during LOCATE
sampling. The 2001 data are taken from Upstill-Goddard et al. (2016).
The implied seawater CH4 concentrations for the Plymouth Sound
sector (Sect. 3.1) are within range of the in situ measurements in the lower
Tamar and near the Plymouth Sound. In contrast, implied seawater
CH4 concentrations for the open-water sector are on average about
4 times higher than the in situ measurements at L4. Thus, while
pCO2 within the open-water flux footprint of the PPAO
agrees reasonably well with pCO2 at L4, this is very
likely not the case for CH4. The differences in salinity (Fig. 9)
and in dissolved oxygen (Fig. S11) indicate that the water masses within the
open-water flux footprint and at L4 are not identical.
Two features of the CH4 concentration and salinity relationship are
particularly relevant for the interpretation of our CH4 flux
measurements. First, the variability in dissolved CH4 concentration
in the Tamar is very large. For example, CH4 concentration at a
salinity of about 30 varies by a factor of 40 during the six transects. The
interannual variation in CH4 concentration during April in 2001,
2017 and 2018 at this salinity is a factor of 12. Secondly, the horizontal
gradient in CH4 concentration near the mouth of the Tamar estuary
is very steep. Observations from April and July 2017 show a slope of between
-20 and -50 nM per salinity unit. Salinity within the open-water flux
footprint varied between 32.2 and 35.2 between September 2015 and
August 2016, while salinity within the Plymouth Sound flux footprint varied
between 32.0 and 35.1. The large range in CH4 concentration and the
strong and variable CH4 and salinity relationship make any
salinity-based prediction of dissolved CH4 concentration within the
flux footprints highly uncertain. Thus, we focus on estimating the transfer
velocity of CO2 but not CH4 in the next section.
<inline-formula><mml:math id="M373" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> gas transfer velocity
The implied pCO2 from EC fluxes and in situ measured
pCO2 agree quite well over the annual cycle for the open-water sector (Fig. 7), suggesting that the use of the wind-speed-dependent
transfer velocity parameterization of Nightingale et al. (2000) is largely
reasonable in the mean. The variability in the implied
pCO2 (as indicated by the 25th and 75th percentiles), however,
is sometimes greater than the variability in the in situ
pCO2. In this section, we estimate the time-varying
CO2 gas transfer velocity (KCO2) and examine its
variability and possible controls.
KCO2 is computed as flux /ΔpCO2/solCO2, where solCO2 is the
solubility of CO2 in water. As shown in Sect. 3.3.2,
pCO2 measured from the open-water flux footprint of PPAO
is comparable to near-coincidental measurements at L4. Thus, to estimate
KCO2 for the open-water sector, we combine pCO2
measurements from the open-water footprint with the more numerous
measurements at L4. To estimate KCO2 for the Plymouth Sound
sector, only pCO2 measurements from that footprint are
used. We linearly interpolate these seawater pCO2
measurements to the times of the hourly CO2 flux measurements.
Interpolation more than 4 days away from the nearest pCO2
observations is discarded. We chose 4 days (ca. half a week) here such that
the computed KCO2 values are retained if made between weekly
pCO2 measurements. The interpolated
pCO2 is then combined with the measured atmospheric
CO2 mixing ratio at PPAO to yield the air–sea
pCO2 difference (ΔpCO2). To
normalize for the effect of temperature, KCO2 is further adjusted
to the Schmidt number of 660 (KCO2,660=KCO2⋅(660/ScCO2)-0.5). The CO2 solubility and
Schmidt number as a function of temperature and salinity are taken from
Wanninkhof et al. (2014). In order to minimize any bias in the computed
KCO2,660 due to the interpolation of daytime only
pCO2 measurements (see Sect. 3.2), we discard the
nighttime (20:00 to 08:00 UTC) KCO2,660 data during times of
expected invasion (i.e. air-to-sea flux). The filtered hourly
KCO2,660 data are then averaged into 6 h bins to reduce random
noise.
Dependence of <inline-formula><mml:math id="M405" display="inline"><mml:mrow><mml:msub><mml:mi>K</mml:mi><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mn mathvariant="normal">660</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> on wind speed and friction
velocity
KCO2,660 is plotted against the 10 m neutral wind speed
(U10n) in Fig. 12, along with a second-order polynomial fit. We have
retained KCO2,660 data here only when the absolute value of
ΔpCO2 exceeded 20 µatm. This threshold is
chosen as a balance between minimizing errors and maximizing data retention.
A higher |ΔpCO2| threshold (e.g.
40 µatm) does not obviously reduce the scatter in the
KCO2,660 and wind speed relationship. Error bars in
KCO2,660 are propagated from the standard errors in the fluxes.
For the open-water sector, KCO2,660 shows a significant non-linear
increase with wind speed (R2=0.35, p<0.0001). The scatter
in the KCO2,660 and wind speed relationship is likely due to a
combination of random uncertainties in the flux measurement (Yang et al.,
2016b) and variability in seawater pCO2 not captured by
the weekly measurements, as well as processes other than wind speed that
affect gas exchange (see below). KCO2,660 for the Plymouth Sound
sector will be discussed in Sect. 3.4.3 within the context of bottom-driven
turbulence.
CO2 transfer velocity (normalized to a
Schmidt number of 660) vs. 10 m neutral wind speed for both the southwest
(open water) and northeast (Plymouth Sound) wind sectors. Note that
colour-coding is capped at |ΔpCO2| values of
80 µatm for clarity.
The mean of the KCO2,660 and wind speed relationship, as
represented by the second-order polynomial fit, agrees (within a 95 %
confidence interval) with the widely used relationship derived by Nightingale
et al. (2000) using the dual-tracer (3He/SF6) technique. We note
that more recent parameterizations of the gas transfer velocity based on
3He/SF6 and radiocarbon budgets (Ho et al., 2006; Sweeney et
al., 2007; Wanninkhof 2014) are largely similar to Nightingale et al. (2000).
In moderate to high winds, measured KCO2,660 increases with wind
speed at a rate that is less than cubic – a power fit yields an exponent
of 1.3. This is generally consistent with other recent closed-path EC
CO2 transfer velocity measurements (Butterworth and Miller, 2016;
Bell et al., 2017; Blomquist et al., 2017; Landwehr et al., 2018).
At wind speeds less than ∼5 m s-1, measured KCO2,660
at the PPAO are sometimes elevated and might not be entirely representative
of air–sea transfer (Yang et al., 2016a). The EC friction velocity in the
open-water sector (see below and in Fig. S2) is also at times higher than
expected at these low wind speeds. The atmosphere was often more unstable at
low wind speeds (z/L of ∼-1), in part because low winds occurred more
frequently during the warmer months. The Kljun et al. (2004) model predicts a
flux footprint that is closer to the PPAO site during these conditions, such
that the near-shore environment (i.e. from the mast to the water's edge)
might have some influence on the fluxes. Furthermore, the double-rotation
method used for the streamline correction of wind may be more uncertain at
lower wind speeds. The planar fit method (Wilczak et al., 2001) could be
superior under these conditions and will be an area of investigation during
future analyses of PPAO flux data.
The friction velocity (u∗), a measure of air–sea total momentum
transfer, is long thought to be a more direct representation of the drivers
of turbulence and gas exchange than wind speed (e.g. Csanady et al., 1990).
This appears to be the case especially for moderately soluble gases that are
not significantly affected by bubble-mediated gas transfer, such as dimethyl
sulfide (Huebert et al., 2010; Yang et al., 2011). The relationship between
KCO2,660 and the EC-derived u∗ shows a slightly better
fit (R2=0.38; Fig. 13) than between KCO2,660 and
U10n (R2=0.35). This is consistent with the idea that
u∗ is a more suitable predictor of K than wind speed. The other
benefit of relating KCO2,660 with u∗ instead of
U10n is that the u∗ measurement may be less affected by
flow distortion than the U10n measurement (Landwehr et al.,
2018).
CO2 transfer velocity (normalized to a
Schmidt number of 660) vs. the friction velocity for both the southwest (open
water) and northeast (Plymouth Sound) wind sectors. Note that colour-coding
is capped at a chlorophyll a concentration of 2 mg m-3 for clarity.
The linear fit from Landwehr et al. (2018), derived from EC measurements of
CO2 flux in the Southern Ocean, is also shown in Fig. 13. Compared
to Landwehr et al. (2018), measurements at PPAO are similar at moderate
u∗ values. At high u∗ values (strong winds), our estimates
of KCO2,660 increase with a greater power. Blomquist et al. (2017)
demonstrated that waves play a role in the open-ocean air–sea exchange of
CO2 at high wind speeds, and we expect waves to also influence
u∗ (e.g. Edson et al., 2013). Waves shoal and steepen when they
approach shallow water at the coast and generally break more frequently than
in the open ocean. KCO2,660 measured at PPAO when waves are large
might not be the same as KCO2,660 over the open ocean.
Unfortunately there were no wave measurements within the flux footprints to
quantitatively investigate this effect.
Seasonal variability in <inline-formula><mml:math id="M459" display="inline"><mml:mrow><mml:msub><mml:mi>K</mml:mi><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mn mathvariant="normal">660</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula>
We might expect the relationship between KCO2,660 and wind speed
to vary in different seasons due to the effects of bubbles and surfactants.
Woolf et al. (1997) and Leighton et al. (2018) suggested an asymmetrical gas
transfer rate that is faster for invasion than for evasion due to the
hydrostatic pressure effect in bubble-mediated gas exchange, which is
important for CO2 (Bell et al., 2017; Blomquist et al., 2017).
Figure 12 is colour-coded by ΔpCO2 (positive when
the ocean is supersaturated). We see that invasion (i.e. air to sea) of
CO2, expected to occur in late spring and summer, was typically
associated with low to moderate wind speeds. Evasion (i.e. sea to air) of
CO2, expected to occur in late autumn and winter, was typically
associated with moderate to high wind speeds. There was limited overlap
between invasion and evasion KCO2,660 cases in the same wind speed
range, partly due to gaps in the pCO2 observations.
Nevertheless, many of the KCO2,660 data were well below the
polynomial fit during periods of expected evasion and when U10n
was between 6 and 10 m s-1.
Recent measurements show large spatial and temporal differences in surfactant
activity over the Atlantic Ocean (Sabbaghzadeh et al., 2017). A higher
surfactant activity has been associated with suppression in the gas transfer
velocity (e.g. Salter et al., 2011; Pereira et al., 2016, 2018). Figure 13 is
colour-coded by the near-surface chlorophyll a concentration (Chl a), an
indicator of phytoplankton biomass and biological activity. Chl a was as
low as 0.2 mg m-3 in the winter and early spring and as high as
5 mg m-3 during late spring and summer. Many of the
KCO2,660 data for the open-water sector were below the polynomial
fit at times of high Chl a concentration. A seasonal variability in
biologically influenced surfactant activity seems likely and could alter the
KCO2,660 and wind speed relationship. Higher-frequency
observations of pCO2 within the flux footprint (e.g. from
a buoy) would greatly increase the number of transfer velocity estimates and
enable a more robust comparison between invasion and evasion. Approaches
similar to Sabbaghzadeh et al. (2017) and Pereira et al. (2016) on a seasonal
scale, coupled with EC gas flux measurements, would help to address the
importance of naturally produced surfactants in gas exchange.
Gas transfer driven by bottom-driven turbulence is parameterized as by Borges
et al. (2004): 1.719 v0.5 h-0.5 (cm h-1), where v is
the current velocity (in cm s-1), and h is water depth (in m). The
authors treat this as a linearly additive term to wind-driven gas exchange.
For a depth of 10 m for the Plymouth Sound and a current velocity on the
order of 1 m s-1 during ebbing and flooding tides (Siddorn et al.,
2003), this leads to a transfer velocity as a result of bottom-driven
turbulence of ∼5 cm h-1 at a Schmidt number of 660. For the open-water sector, gas transfer driven by bottom-driven turbulence is calculated
to be less than 4 cm h-1 due to the deeper water. For reference, the
Nightingale et al. (2000) parameterization at a wind speed of
6–9 m s-1 is about 10–20 cm h-1. Thus, bottom-driven
turbulence may have a relatively large (∼25 %) influence on our
observations of KCO2,660 at low to moderate wind speeds.
Neglecting bottom-driven turbulence could have resulted in overestimates when
calculating implied GHG concentrations (Sect. 3.1, 3.2), particularly at low
wind speeds. Note though that our calculations of implied GHG concentrations
were limited to wind speeds > 5 m s-1.
KCO2,660 derived for the Plymouth Sound sector is also shown in
Figs. 12 and 13. Given the strong diurnal variability in the implied
pCO2 for this wind sector (see Fig. 8), we have further
limited KCO2,660 to the time of day of 10:00 to 16:00 UTC. This
strict filtering as well as the small number of coincidental flux and
pCO2 measurements results in only five 6 h
KCO2,660 estimates for the Plymouth Sound sector. Plymouth Sound
KCO2,660 values roughly increase with wind speed and friction
velocity and are within the range of variability of the open-water
KCO2,660 values. Note that four out of five of these
KCO2,660 estimates were associated with wind speeds over
9 m s-1, for which bottom-driven turbulence is expected to have less
influence (≤25 % of the wind-driven KCO2,660). Future
studies that combine EC flux measurements, frequent observations of seawater
CO2 and CH4 concentrations within the footprint and in
situ measurements of current velocity would allow us to better test and
improve K parameterizations in shallow water.
Effects of rain on air–sea <inline-formula><mml:math id="M508" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> exchange
Our year-long EC flux observations provide a valuable opportunity to directly
assess the importance of rain on gas exchange. Mechanistically, rain could
affect air–sea CO2 flux in at least three ways. First, lab studies show that the
falling raindrops increase the near-surface turbulence, increasing total K
(e.g. Ho et al., 1997; Zappa et al., 2009). This effect is relatively more
important at low wind speeds (e.g. Harrison et al., 2012). Secondly,
rainwater could reduce near-surface pCO2 via changes in
the carbonate chemistry and gas solubility (e.g. dilution effect; Turk et
al., 2010) and so result in more negative (or less positive) CO2
fluxes. Lastly, dissolved CO2 in rain droplets is taken up by the
sea, which is often termed the wet-deposition flux (e.g. Ashton et al.,
2016). We examine each of these three mechanisms below.
Figure S12 shows the hourly KCO2,660 and wind speed for the open-water sector, colour-coded by the measured precipitation rate at the surface
(Ps). We use the hourly KCO2,660 data here (filtered
by a |ΔpCO2|≥20µatm threshold)
because rainfall is highly episodic. It is not obvious from our data that
rain enhances K at a given wind speed, which could be in part because
typical rain rates at PPAO are roughly 1 order of magnitude lower than in lab
studies or parts of the tropics where rain rates are often tens of
millimetres per hour. A caveat here is that the pCO2 measurements
were made approximately once a week from ∼3 m depth. Thus, they do not
fully describe short-term changes in pCO2 at the air–sea
interface as a result of rain. This could in turn influence the K estimate.
<italic>Dilution effect on near-surface</italic> <inline-formula><mml:math id="M525" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="italic">pCO</mml:mi><mml:mn mathvariant="italic">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>
To tease out the effect of rain on CO2 flux via the dilution effect
(and not on K), we focus on periods where we do not ordinarily expect to
see much flux (i.e. when the expected |ΔpCO2| is
approximately zero). Figure S13 shows the hourly CO2 flux vs. rain rate
for the open-water wind sector. Here we have only retained data where the
expected |ΔpCO2| is within 10 µatm.
Within our limited dataset and given the measurement uncertainties, it is not
obvious that rain makes the CO2 flux more negative (or less
positive) via the dilution effect. For the open-water sector with |ΔpCO2|≤10µatm, the mean
CO2 flux during rainy periods was -5.3 (SE of
5.1) mmol m-2 d-1. During non-rainy periods, the mean
CO2 flux was -2.1 (SE of 2.1) mmol m-2 d-1. The two
estimates are not statistically different from each other or from zero.
<italic>Wet-deposition flux</italic>
The wet-deposition flux of CO2 is estimated on an hourly basis as
-solCO2⋅CO2,a⋅Ps. Here it is
assumed that the falling rain droplets are in equilibrium with atmospheric
CO2 (CO2,a). The mean wet-deposition flux over the entire
year (including rainy and non-rainy periods) was computed to be about
-0.1 mmol m-2 d-1, which is orders of magnitude smaller than
the air–sea gas flux (e.g. Fig. 5). During rainy periods, the mean
wet-deposition flux was -0.4 mmol m-2 d-1. Overall, the impact
of rain on air–sea CO2 exchange is fairly limited at PPAO, largely
as a result of the modest rain rate.
Conclusions
Air–sea CH4 and CO2 fluxes measured by eddy covariance
from a coastal location in the southwest UK over 1 year demonstrate
significant variability on seasonal timescales. CH4 flux in the
coastal seas varied on a semi-diurnal (i.e. tidal) scale, while CO2
flux at times varied diurnally. These observations suggest that sporadic
samplings of seawater concentrations that are limited to certain seasons,
times of the day or tidal cycle could result in biased annual mean flux
estimates (see Sect. 3.1 and 3.2). Surface ocean CH4 saturations
implied from the measured fluxes exceed a few hundred percent, and were
higher over the semi-enclosed Plymouth Sound than over open water. These
results are consistent with the trend in dissolved CH4
concentration observed from the upper part of the river Tamar to the mouth of
the Plymouth Sound. The coastal sea was a net sink of CO2 in late
spring and summer and a net source of CO2 in autumn and winter.
CO2 flux from the Plymouth Sound demonstrated greater diurnal
variability than the CO2 flux from the open-water sector. We
estimate the CO2 transfer velocity from our measurements of fluxes
and in situ seawater concentrations. The mean derived CO2 transfer
velocity at this coastal location agrees reasonably well with previous
tracer-based and closed-path CO2 eddy covariance estimates from the
open ocean. Rainfall does not appear to have a large direct effect on air–sea
CO2 exchange at our temperate coastal site. There are hints of
seasonality in the transfer velocity and wind speed relationship that may be
related to asymmetric bubble-mediated gas exchange or biologically derived
surfactants. The effect of bubbles, surfactants and bottom-driven turbulence
warrants further investigation in order to improve our understanding of air–sea
gas exchange and estimates of coastal greenhouse gas budgets.
Data availability
Penlee Point Atmospheric Observatory
(PPAO) data are archived at the Centre for Environmental Data Analysis
(CEDA):
http://catalogue.ceda.ac.uk/uuid/8f1ff8ea77534e08b03983685990a9b0 (last
access: 7 March 2019; Bell et al., 2017). Interested readers can contact the
corresponding author directly for the full high-frequency (10 Hz) dataset.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-16-961-2019-supplement.
Author contributions
MY and TGB designed and performed the flux measurements and data
analysis and interpretation. IJB and APR measured dissolved CH4
concentration, while VK measured seawater pCO2. JRF and
TJS supplied the underway and buoy data from the Western Channel Observatory.
TJS and PN provided helpful comments on the focus and context of the paper.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
This work contributes to the ACSIS (The North Atlantic Climate System
Integrated Study; NE/N018044/1), MOYA (Methane Observations and Yearly
Assessments; NE/N015932/1), LOCATE (Land Ocean Carbon Transfer; NE/N018087/1)
and CLASS (Climate Linked Atlantic Sector Science) projects funded by the
Natural Environment Research Council (NERC), UK. The Western Channel
Observatory is funded by NERC's National Capability programme. Trinity House
(http://www.trinityhouse.co.uk/, last access: 7 March 2019) owns the
Penlee site and has kindly agreed to rent the building to PML so that
instrumentation can be protected from the elements. We are able to access
the site thanks to the cooperation of Mount Edgcumbe Estate
(http://www.mountedgcumbe.gov.uk/, last access: 7 March 2019). We thank
the Environmental Agency for the Tamar flow data. We also thank
Frances E. Hopkins (PML), Margaret J. Yelland (National Oceanography Centre),
Ian M. Brooks (University of Leeds) and John Prytherch (Stockholm University)
for continued measurement support. This is contribution number 5 from the
Penlee Point Atmospheric Observatory. Edited
by: Gwenaël Abril Reviewed by: two anonymous referees
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